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​​​​​​​​​​​​​​​​​​​​​Dynamic Probabilistic Risk Assessment Research


​​​G​oal

To develop and demonstrate a dynamic probabilistic risk assessment (PRA) for use in nuclear plant safety analyses.

Dynamic PRA, like traditional PRA, evaluates risk, likelihood and consequences of accident scenarios. The major difference between dynamic and static PRA is that dynamic PRA can explicitly integrate time and physical phenomena into risk consideration while traditional PRA considers time only implicitly (e.g., via assumptions or success criteria).

Outcome

Researchers will develop a flexible and comprehensive platform to handle applications of dynamic PRA. The platform will have robust properties and features enabling it to obtain probabilistic results, and to gather dynamic benefits such as timing and event sequences for specified simulated conditions. Software is developed by using an open standard for communication, which allows for coupling to other PRA (e.g., external hazard modeling), or physics-based (e.g., thermo-hydraulic analysis) software. The two main software tools used for dynamic PRA modeling are EMRALD and RAVEN.

Planned Major Accomplishments​

  • ​2023—Continue research and development of a dynamic PRA in close collaboration with the industry.

  • 2024—Expand capabilities of the dynamic PRA tool to address industry needs.

Related Reports​

 

 

Integration of Physical Security Simulation Software Applications in a Dynamic Risk Framework, INL/EXT-21-64333221385Integration of Physical Security Simulation Software Applications in a Dynamic Risk Framework, INL/EXT-21-64333Integration of Physical Security Simulation Software Applications in a Dynamic Risk Framework, INL/EXT-21-643339/8/2021 5:20:28 PMINL/EXT-21-64333 Revision 0 Light Water Reactor Sustainability Program Integration of Physical Security Simulation Software Applications in a Dynamic Risk Framework August 2021 122https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf
Methodology and Application of Physical Security Effectiveness Based on Dynamic Force-on-Force Modeling, INL/EXT-20-59891221259Methodology and Application of Physical Security Effectiveness Based on Dynamic Force-on-Force Modeling, INL/EXT-20-59891Methodology and Application of Physical Security Effectiveness Based on Dynamic Force-on-Force Modeling, INL/EXT-20-598919/30/2020 9:58:38 PMINL/EXT-20-59891 Light Water Reactor Sustainability Program Methodology and Application of Physical Security Effectiveness Based on Dynamic Force-on-Force Modeling September 2020 89https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf
Integration of FLEX Equipment and Operator Actions in Plant Force-On-Force Models with Dynamic Risk Assessment, INL/EXT-20-59510221382Integration of FLEX Equipment and Operator Actions in Plant Force-On-Force Models with Dynamic Risk Assessment, INL/EXT-20-59510Integration of FLEX Equipment and Operator Actions in Plant Force-On-Force Models with Dynamic Risk Assessment, INL/EXT-20-595108/27/2020 1:15:47 AMU.S. Department of Energy Office of Nuclear Energy This information was prepared as an account of work sponsored by an agency of the U.S. Government Labor costs continue to rise in 94https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf
Status of Adaptive Surrogates within the RAVEN Framework, INL/EXT-17-43438269299The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies.The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies.11/6/2017 9:29:14 PMINL/EXT-17-43438 Light Water Reactor Sustainability Program Status of Adaptive Surrogates within the RAVEN framework Andrea Alfonsi, Congjian Wang, Joshua Cogliati, Diego 39https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf
A Simulation Based Dynamic Analysis Approach for Modeling Total Plant Response to Flooding Events, INL/EXT-17-40928221400A Simulation-Based Dynamic Analysis Approach for Modeling Total Plant Response to Flooding Events, RIL 2022-03 INL/EXT-17 40928A Simulation-Based Dynamic Analysis Approach for Modeling Total Plant Response to Flooding Events, RIL 2022-03 INL/EXT-17 409284/29/2022 4:04:31 PMResearch Information Letter Office of Nuclear Regulatory Research This report was prepared as Idaho National Laboratory Report 68https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf
System Reliability Analysis Capability and Surrogate Model Application in RAVEN, INL/EXT-16-37243269300This report describes the effort performed to improve the analysis capabilities of the RAVEN code. These efforts include improving the reliability (or “limit”) surface search of the RAVEN code and exploring new opportunities in usage of surrogate models by extending the current RAVEN capabilities to multi-physics surrogate models construction for high-dimensionality problems.This report describes the effort performed to improve the analysis capabilities of the RAVEN code. These efforts include improving the reliability (or “limit”) surface search of the RAVEN code and exploring new opportunities in usage of surrogate models by extending the current RAVEN capabilities to multi-physics surrogate models construction for high-dimensionality problems.7/27/2017 8:30:18 PMINL/EXT-16-37243 Light Water Reactor Sustainability Program System Reliability Analysis Capability and Surrogate Model Application in RAVEN Cristian Rabiti, Andrea Alfonsi 48https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf
Risk-Informed Safety Margin Characterization Methods Development Work, INL/EXT-14-33191269301This report presents several analyses that demonstrate the value of the RISMC approach in order to assess risk associated with nuclear power plants (NPPs). We focus on simulation-based PRA which, in contrast to classical PRA, heavily employs system simulator codes. First, we compare, these two types of analyses, classical and RISMC, for a Boiling Water Reactor (BWR) Station Black Out (SBO) initiating event.This report presents several analyses that demonstrate the value of the RISMC approach in order to assess risk associated with nuclear power plants (NPPs). We focus on simulation-based PRA which, in contrast to classical PRA, heavily employs system simulator codes. First, we compare, these two types of analyses, classical and RISMC, for a Boiling Water Reactor (BWR) Station Black Out (SBO) initiating event.9/30/2014 9:34:17 PMINL/EXT-14-33191 Light Water Reactor Sustainability Program Risk-Informed Safety Margin Characterization Methods Development Work September 2014 DOE Office of Nuclear Energy 52https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf
Advanced probabilistic risk analysis using RAVEN and RELAP-7, INL/EXT-14-32491269302Advanced probabilistic risk analysis using RAVEN and RELAP-7, INL/EXT-14-32491Advanced probabilistic risk analysis using RAVEN and RELAP-7, INL/EXT-14-324918/17/2015 8:43:08 PM7KH,1/LVD86'HSDUWPHQWRI(QHUJ\1DWLRQDO/DERUDWRU\ RSHUDWHGE\%DWWHOOH(QHUJ\$OOLDQFH ,1/(;7 Advanced Probabilistic Risk Analysis Using RAVEN and RELAP-7 46https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf
Support and Modeling for the Boiling Water Reactor Station Black Out Case Study Using RELAP and RAVEN, INL/EXT-13-30203269303The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these two factors on the safety of the plant, the RISMC project aims to provide insight to decision-makers through a series of simulations of the plant dynamics for different initial conditions.The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these two factors on the safety of the plant, the RISMC project aims to provide insight to decision-makers through a series of simulations of the plant dynamics for different initial conditions.12/20/2013 4:26:24 PMThe INL is a U.S. Department of Energy National Laboratory operated by Battelle Energy Alliance INL/EXT-13-30203 Light Water Reactor Sustainability Program Support and Modeling 48https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf
Reactor analysis and virtual control environment (RAVEN) FY12, INL/EXT-12-27351269304RAVEN is a complex software tool that has functionality spanning from being the RELAP-7 user interface, to using RELAP-7 to perform Risk Informed Safety Characterization (RISMC), and to controlling RELAP-7 calculation execution.RAVEN is a complex software tool that has functionality spanning from being the RELAP-7 user interface, to using RELAP-7 to perform Risk Informed Safety Characterization (RISMC), and to controlling RELAP-7 calculation execution.10/8/2012 9:42:12 PMThe INL is a U.S. Department of Energy National Laboratory operated by Battelle Energy Alliance INL/EXT-12-27351 Reactor Analysis and Virtual Control Environment (RAVEN) FY12 52https://lwrs.inl.gov/RiskInformed Safety Margin Characterization/Forms/AllItems.aspxpdfFalsepdf

​For more information contact:

Svetlana (Lana) Lawrence
Risk-Informed Systems Analysis, Pathway Lead
Idaho National Laboratory

simulation-based risk.jpg 

Schematic showing the concept of a simulation-based risk assessment of various stages and transitions from stage to stage.